Job cuts or response to shortage of skilled workers?
Nothing works without artificial intelligence (AI) anymore. At least, that's the impression you get when you browse the websites of software manufacturers, relevant IT publications, company annual reports or social networks. And this impression is not entirely wrong: The "KI Monitor" of the Bundesverband Digitale Wirtschaft (BVDW) establishes an AI index that attests to an increased relevance for AI over the last few years. And the area of application of AI also extends across the most diverse areas of private or professional life: assistance systems in cars, medical diagnostics, biometric recognition, predictive maintenance in industry - all of these would be almost inconceivable today without AI with its categories of machine learning, deep learning or neural networks. Even the software used by plagiarism hunters, which cost some politicians their doctorates, is of course AI-supported.
Now, one might argue that AI existed years ago. Chess computers have been around for more than 30 years, and data mining entered IT in the late 1990s. Nevertheless, it cannot be denied that AI processes have been further developed, refined and made far more effective in the last ten years in particular, which has to do with Big Data, the expansion of IT infrastructures or even cloud models.
AI is supposed to increase efficiency in companies. A nice (side) effect is to relieve people in their professional world so that they can concentrate on essential, value-adding activities. Does AI thus also promote job cuts when algorithms increasingly take over the activities of humans? That is certainly not to be dismissed out of hand. Nevertheless, AI will never be able to completely replace humans. As a rule, AI processes work retrospectively: they analyze processes and procedures of the past in order to derive actions for the present. Although humans do nothing fundamentally different, they also use empathy, networked thinking, creativity and cognitive flexibility. And this is where AI reaches its limits.
An example from the finance area, the accounts payable, i.e. the invoice receipt process. AI has been used here for some time to increase the read rates when using OCR for paper and PDF invoices. The idea is to save the accounting department the hassle of entering invoices into the SAP system. Instead, the accounting department can take care of accounting regulations or more complex operations such as asset accounting, depreciation or periodic consolidations.
Master of the processes
But AI does not stop at OCR processes alone. AI is now also used for automated account assignments for FI documents or for managing discrepancies between invoice, purchase order and goods receipt. Still, accounting needs it to regularly check tax compliance (GoBD), intervene in case of exceptions, and ultimately be the master of the process. Accounting on autopilot - that's impossible for tax compliance reasons alone. AI may well help to reduce accounting jobs, but these are mostly jobs that are already difficult to fill due to the state of the labor market. Already, as in other areas of work, one hears complaints from finance managers that employees leaving due to age are hard to replace.
Is this view too optimistic? The next few years will show whether departments need to feel threatened by AI. Certain expertise can certainly be replaced by AI, but humans themselves are unlikely to be. To stay with the image of the autopilot: Even when a machine is flying on autopilot, there are still crew members in the cockpit.
